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Interaction between hairy surfaces and turbulence for different surface time scales

Published online by Cambridge University Press:  27 December 2018

Johan Sundin Open the ORCID record for Johan Sundin [Opens in a new window]  and
Shervin Bagheri Open the ORCID record for Shervin Bagheri [Opens in a new window]
Johan Sundin
Affiliation:
Linné FLOW Centre, KTH Mechanics, Royal Institute of Technology, SE-100 44 Stockholm, Sweden
Shervin Bagheri*
Affiliation:
Linné FLOW Centre, KTH Mechanics, Royal Institute of Technology, SE-100 44 Stockholm, Sweden
*
†Email address for correspondence: [email protected]
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Abstract

Surfaces with filamentous structures are ubiquitous in nature on many different scales, ranging from forests to micrometre-sized cilia in organs. Hairy surfaces are elastic and porous, and it is not fully understood how they modify turbulence near a wall. The interaction between hairy surfaces and turbulent flows is here investigated numerically in a turbulent channel flow configuration at friction Reynolds number $Re_{\unicode[STIX]{x1D70F}}\approx 180$. We show that a filamentous bed of a given geometry can modify a turbulent flow very differently depending on the resonance frequency of the surface, which is determined by the elasticity and mass of the filaments. Filaments having resonance frequencies lower than the main frequency content of the turbulent wall-shear stress conform to slowly travelling elongated streaky structures, since they are too slow to adapt to fluid forces of higher frequencies. On the other hand, a bed consisting of stiff and low-mass filaments has a high resonance frequency and shows local regions of increased permeability, which results in large entrainment and a vast increase in drag.

JFM classification

Flow Control: Flow Control Turbulent Flows: Turbulent boundary layers
Type
JFM Papers
Information
Journal of Fluid Mechanics , Volume 861 , 25 February 2019 , pp. 556 - 584
Copyright
© 2018 Cambridge University Press 

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References

Battiato, I., Bandaru, P. R. & Tartakovsky, D. M. 2010 Elastic response of carbon nanotube forests to aerodynamic stresses. Phys. Rev. Lett. 105 (14), 144504.Google Scholar
Bisshopp, K. E. & Drucker, D. C. 1945 Large deflection of cantilever beams. Q. Appl. Maths 3 (3), 272–275.Google Scholar
Brandt, A. 2011 Noise and Vibration Analysis: Signal Analysis and Experimental Procedures. Wiley.Google Scholar
Breugem, W. P., Boersma, B. J. & Uittenbogaard, R. E. 2006 The influence of wall permeability on turbulent channel flow. J. Fluid Mech. 562, 35–72.Google Scholar
Brücker, C. 2011 Interaction of flexible surface hairs with near-wall turbulence. J. Phys.: Condens. Matter 23 (18), 184120.Google Scholar
Brücker, C., Bauer, D. & Chaves, H. 2007 Dynamic response of micro-pillar sensors measuring fluctuating wall-shear-stress. Exp. Fluids 42 (5), 737–749.Google Scholar
Chopard, B., Kontaxakis, D., Lagrava, D., Latt, J., Malaspinas, O., Parmigiani, A., Rybak, T. & Sagon, Y.2015 The palabos project. FlowKit Ltd (http://www.palabos.org/).Google Scholar
De Langre, E. 2008 Effects of wind on plants. Annu. Rev. Fluid Mech. 40, 141–168.Google Scholar
Do-Quang, M., Amberg, G., Brethouwer, G. & Johansson, A. V. 2014 Simulation of finite-size fibers in turbulent channel flows. Phys. Rev. E 89 (1), 013006.Google Scholar
Dorschner, B., Chikatamarla, S. S., Bösch, F. & Karlin, I. V. 2015 Grad’s approximation for moving and stationary walls in entropic lattice Boltzmann simulations. J. Comput. Phys. 295, 340–354.Google Scholar
Favier, J., Dauptain, A., Basso, D. & Bottaro, A. 2009 Passive separation control using a self-adaptive hairy coating. J. Fluid Mech. 627, 451–483.Google Scholar
Freund, R. J., Wilson, W. J. & Mohr, D. L. 2010 Statistical Methods. Academic Press.Google Scholar
Gopinath, A. & Mahadevan, L. 2011 Elastohydrodynamics of wet bristles, carpets and brushes. Proc. R. Soc. Lond. A 467 (2130), 20100228.Google Scholar
Gosselin, F. P. & De Langre, E. 2011 Drag reduction by reconfiguration of a poroelastic system. J. Fluid. Struct. 27 (7), 1111–1123.Google Scholar
Guo, Z., Zheng, C. & Shi, B. 2002 Discrete lattice effects on the forcing term in the lattice Boltzmann method. Phys. Rev. E 65 (4), 046308.Google Scholar
Hansen, M. O. 2015 Aerodynamics of Wind Turbines. Routledge.Google Scholar
Hu, Z., Morfey, C. L. & Sandham, N. D. 2006 Wall pressure and shear stress spectra from direct simulations of channel flow. AIAA J. 44 (7), 1541–1549.Google Scholar
Itoh, M., Tamano, S., Iguchi, R., Yokota, K., Akino, N., Hino, R. & Kubo, S. 2006 Turbulent drag reduction by the seal fur surface. Phys. Fluids 18 (6), 065102.Google Scholar
Jiménez, J. & Moin, P. 1991 The minimal flow unit in near-wall turbulence. J. Fluid Mech. 225, 213–240.Google Scholar
Jimenez, J., Uhlmann, M., Pinelli, A. & Kawahara, G. 2001 Turbulent shear flow over active and passive porous surfaces. J. Fluid Mech. 442, 89–117.Google Scholar
Kim, E. & Choi, H. 2014 Space–time characteristics of a compliant wall in a turbulent channel flow. J. Fluid Mech. 756, 30–53.Google Scholar
Krüger, T., Kusumaatmaja, H., Kuzmin, A., Shardt, O., Silva, G. & Viggen, E. M. 2017 The Lattice Boltzmann Method. Springer.Google Scholar
Kuwata, Y. & Suga, K. 2016 Imbalance-correction grid-refinement method for lattice Boltzmann flow simulations. J. Comput. Phys. 311, 348–362.Google Scholar
Lācis, U., Zampogna, G. A. & Bagheri, S. 2017 A computational continuum model of poroelastic beds. Proc. R. Soc. Lond. A 473 (2199), 20160932.Google Scholar
Lagrava, D., Malaspinas, O., Latt, J. & Chopard, B. 2012 Advances in multi-domain lattice Boltzmann grid refinement. J. Comput. Phys. 231 (14), 4808–4822.Google Scholar
Latt, J., Chopard, B., Malaspinas, O., Deville, M. & Michler, A. 2008 Straight velocity boundaries in the lattice Boltzmann method. Phys. Rev. E 77, 056703.Google Scholar
Lee, M. & Moser, R. D. 2015 Direct numerical simulation of turbulent channel flow up to Re 𝜏 ≈ 5200. J. Fluid Mech. 774, 395–415.Google Scholar
Lindström, S. B. & Uesaka, T. 2007 Simulation of the motion of flexible fibers in viscous fluid flow. Phys. Fluids 19 (11), 113307.Google Scholar
Liu, G., Wang, A., Wang, X. & Liu, P. 2016 A review of artificial lateral line in sensor fabrication and bionic applications for robot fish. Appl. Bionics Biomech. 2016, 4732703.Google Scholar
Nepf, H. M. 2012 Flow and transport in regions with aquatic vegetation. Annu. Rev. Fluid Mech. 44, 123–142.Google Scholar
Orlandi, P. & Leonardi, S. 2006 DNS of turbulent channel flows with two- and three-dimensional roughness. J. Turbul. 7 (7), N73.Google Scholar
Orlandi, P., Leonardi, S., Tuzi, R. & Antonia, R. A. 2003 Direct numerical simulation of turbulent channel flow with wall velocity disturbances. Phys. Fluids 15 (12), 3587–3601.Google Scholar
Perot, B. & Moin, P. 1995 Shear-free turbulent boundary layers. Part 1. Physical insights into near-wall turbulence. J. Fluid Mech. 295, 199–227.Google Scholar
Peskin, C. S. 2002 The immersed boundary method. Acta Numerica 11, 479–517.Google Scholar
Pope, S. B. 2001 Turbulent Flows. IOP Publishing.Google Scholar
Ross, R. F. & Klingenberg, D. J. 1997 Dynamic simulation of flexible fibers composed of linked rigid bodies. J. Chem. Phys. 106 (7), 2949–2960.Google Scholar
Rosti, M. E. & Brandt, L. 2017 Numerical simulation of turbulent channel flow over a viscous hyper-elastic wall. J. Fluid Mech. 830, 708–735.Google Scholar
Rosti, M. E., Brandt, L. & Pinelli, A. 2018 Turbulent channel flow over an anisotropic porous wall–drag increase and reduction. J. Fluid Mech. 842, 381–394.Google Scholar
Schmid, C. F., Switzer, L. H. & Klingenberg, D. J. 2000 Simulations of fiber flocculation: Effects of fiber properties and interfiber friction. J. Rheol. 44 (4), 781–809.Google Scholar
Skotheim, J. M. & Mahadevan, L. 2004 Soft lubrication. Phys. Rev. Lett. 92 (24), 245509.Google Scholar
Skotheim, J. M. & Mahadevan, L. 2005 Soft lubrication: the elastohydrodynamics of nonconforming and conforming contacts. Phys. Fluids 17 (9), 092101.Google Scholar
Tao, J. & Yu, X. B. 2012 Hair flow sensors: from bio-inspiration to bio-mimicking – a review. Smart Mater. Struct. 21 (11), 113001.Google Scholar
Wan, F., Ye, Q., Yu, B., Pei, X. & Zhou, F. 2013 Multiscale hairy surfaces for nearly perfect marine antibiofouling. J. Mater. Chem. B 1 (29), 3599–3606.Google Scholar
Wu, J. & Aidun, C K. 2010a A method for direct simulation of flexible fiber suspensions using lattice Boltzmann equation with external boundary force. Intl J. Multiphase Flow 36 (3), 202–209.Google Scholar
Wu, J. & Aidun, C. K. 2010b Simulating 3D deformable particle suspensions using lattice Boltzmann method with discrete external boundary force. Intl J. Numer. Meth. 62 (7), 765–783.Google Scholar
Yamamoto, S. & Matsuoka, T. 1993 A method for dynamic simulation of rigid and flexible fibers in a flow field. J. Chem. Phys. 98 (1), 644–650.Google Scholar